Kaixiong Gong

Towards Unified and Effective Domain Generalization

2023 · arXiv (Cornell University)

We propose $\textbf{UniDG}$, a novel and $\textbf{Uni}$fied framework for $\textbf{D}$omain $\textbf{G}$eneralization that is capable of significantly enhancing the out-of-distribution generalization performance of foundation models regardless of their architectures. The core idea of UniDG is to …

Source-Free Active Domain Adaptation via Augmentation-Based Sample Query and Progressive Model Adaptation

2023 · IEEE Transactions on Neural Networks and Learning Systems

Active domain adaptation (ADA), which enormously improves the performance of unsupervised domain adaptation (UDA) at the expense of annotating limited target data, has attracted a surge of interest. However, in real-world applications, the source data …